The exemplary embodiment relates to a system and method for recommending items in multi-relational environments such as social networks. Social networks are represented logically as relational graphs where entities belonging to the social networks are linked by one or more relations.
Large social media networks such as media sharing sites Flickr and YouTube contain many (e.g., billions) of images and videos uploaded and annotated by many (e.g., millions) of users. The ability to tag media objects (such as images and videos) within social networks is a powerful mechanism for improving media sharing and search facilities. In such social networks, tags play the role of metadata for the associated media objects. However, these tags are often provided in a free form reflecting an individual user's unique perception of a media object rather than a uniform and consistent methodology for identifying and tagging on object. The lack of uniformity in tagging can reduce the effectiveness of searching based on tags, since the searcher and the tagger may employ different terminology. Despite this free individual choice, some common usage topics emerge when people agree on the semantic description of a given media object or a group of objects.
In the case of media sharing sites such as Flickr and YouTube, the wealth of annotated and tagged objects on the sites form a base for suggesting tags for new and existing media objects. Recommendation systems are particularly useful in bootstrap and querying modes. In the bootstrap mode, a recommendation system suggests the most relevant tags for newly uploaded objects. In the query mode, a user annotating an image is presented with recommended tags that can augment the existing image tags. Both modes can ease the annotation task for the user and help expand the coverage of the tags annotating the images.
In a broader sense, the activity on social network sites often spans along multiple dimensions involving a variety of entity types (e.g. “entities”) and relationships (relations) between them. Thus, tag recommendation is just one of many possible scenarios of recommending data to a user of a social networking site based on meta-data of other social network objects. For example, other recommendation scenarios may concern recommending contacts or a group for a user, recommending an image for a group, etc. These recommendations may be provided based on multiple relationships between entities in a social network. Accordingly, it is desirable to know, for a given recommendation task, which relations between entities are relevant to the recommendation task and how the relations are used to recommend items in an optimal manner.